1. Field of the Invention
The present invention relates generally to estimation of economic loss distributions and measures of these distributions such as Average Annual Loss (AAL) and Probable Maximal Loss (PML) due to wind storms, and more specifically to systems and methods for estimating economic loss distributions due to tropical cyclones (hurricanes and typhoons).
2. Background Information
The development of catastrophe models that can generate a loss exceedance probability curve for a portfolio greatly expands the underwriting options available to insurers. A portfolio manager can use a catastrophe model to calculate the probability that the portfolio loss will exceed a given level or to calculate the probability of experiencing a loss that exceeds the company's survival constraint. The insurer could also examine the effect of changing deductibles and coverage limits on the existing portfolio.
An underwriter's decision to write a new account is based on the magnitude of the risk, its correlation with the existing portfolio, and the highest acceptable price that a client is willing to pay for insurance. In addition, there are factors related to what is being insured (e.g., flammability of a structure, performance of the structure type under wind or earthquake loads), location of the structure (e.g., distance from the coast or to active faults, potential for ground failures such as landslides), and how much can be charged (i.e., regulatory constraints and competitive impacts on rates for a given policy form).
Given a particular event, a catastrophe model is used to calculate a ground-up loss for a particular structure within a portfolio. Since the event is random, an annual rate of occurrence is associated with the structure and, by extension, with the calculated losses. For all possible events with their occurrence rates, calculations of all losses associated with each event can be completed.
Recently, catastrophe risk management companies have become increasingly interested in modeling the wind field of a landfalling hurricane at the highest level possible. A high resolution wind field model is a critical component for assessing prospective property losses in affected coastal and inland areas. During a landfalling hurricane, the wind speeds at a particular location change direction and intensity as the hurricane approaches, and are further impacted by surface roughness features upwind as the storm interacts with land. In order to model wind speeds as accurately as necessary to assess property losses, a high degree of precision in modeling terrain and land use features is required.
Industry standard catastrophe models, such as the Hazus Hurricane Model, use various methods for estimating roughness length based on Land Use Land Cover (LULC) type for an area from one of several available government databases, and then assigning a roughness length to that LULC type. The five Florida Water Management Districts (FWMD) maintain LULC databases that collectively cover the entire state. The data source for the past and current versions of these databases is the National Aerial Photography Program's 1:40,000 scale infrared imagery. Each LULC classification has been assigned a roughness length value by comparing sample LULC classes with aerial photographs of the same location.
The most nationally consistent and up-to-date source of land-use data in the United States is the National Land Cover Data compiled by the Multi-Resolution Land Characteristics (MRLC) Consortium. This is a partnership of six federal environmental monitoring programs along with the EROS Data Center of the U.S. Geological Survey. Their goal was to combine their resources in purchasing Landsat satellite imagery and to use the experience, expertise, and resources of the respective programs to generate LULC data and functional land characteristics databases for the United States. The categories of the MRLC LULC data have been mapped to roughness length values using the same aerial photography approach used to assign roughness length values to the FWMD LULC data.
The Risk Management Solutions United States Hurricane Model (RMS USHU) uses National Land Cover Data (NLCD 92), derived from high resolution satellite data, to approach the problem of accurately modeling the land terrain features and the effect of surface roughness on wind speeds. In order to calculate the effects of surface roughness changes on both mean and gust wind speeds, a surface roughness database containing information on both the surface roughness and its geographical variation is required. This is typically achieved through the use of a ground roughness database that identifies a number of different Land Use/Land Cover (LULC) types. Each land use/land cover type is subsequently mapped to a characteristic roughness length value based primarily on known classification schemes, such as open water, snow/barren, grassland, standard countryside, cultivated countryside, forest, suburban, high density suburban, city center, and skyscraper.
However, seemingly small differences in design and input can significantly impact modeled losses. Hence, the choice of loss model will impact insurer pricing. The imprecision of such modeling apparent in that for any given classification scheme, the model will assign a single roughness length value. However, industry standards indicated that for any given classification scheme, the roughness length for a particular classification scheme can fall within a range of values. It is further known that the AAL for a building in an area with roughness length of, for example, 0.2 will be more than twice that for the same building in an area with a roughness length of 0.5. Accordingly, there is a need for an improved model to more accurately estimate the true roughness length around a particular structure in order to more accurately estimate the AAL therefor.